arXiv subjects

Ricard V. Sole

Publications and source records attributed to Ricard V. Sole.

At least 19 recordsLinked to original sources

arXiv2013

Red Queen Coevolution on Fitness Landscapes

Species do not merely evolve, they also coevolve with other organisms. Coevolution is a major force driving interacting species to continuously evolve ex- ploring their fitness landscapes. Coevolution involves the coupling of species fit- ness landscapes, linking species genetic changes with their inter-specific ecological interactions. Here we first introduce the Red Queen hypothesis of evolution com- menting on some theoretical aspects and empirical evidences. As an introduction to the fitness landscape concept, we review key issues on evolution on simple and rugged fitness landscapes. Then we present key modeling examples of coevolution on different fitness landscapes at different scales, from RNA viruses to complex ecosystems and macroevolution.

nlin.AO↗

arXiv2007

Consciousness, brains and the replica problem

Although the conscious state is considered an emergent property of the underlying brain activity and thus somehow resides on brain hardware, there is a non-univocal mapping between both. Given a neural hardware, multiple conscious patterns are consistent with it. Here we show, by means of a simple {\em gedankenexperiment} that this has an important logic consequence: any scenario involving the transient shutdown of brain activity leads to the irreversible death of the conscious experience. In a fundamental way, unless the continuous stream of consciousness is guaranteed, the previous self vanishes and is replaced by a new one.

nlin.AO↗

arXiv2007

Hierarchical Small Worlds in Software Architecture

In this paper, we present a complex network approach to the study of software engineering. We have found universal network patterns in a large collection of object-oriented (OO) software systems written in C++ and Java. All the systems analyzed here display the small-world behavior, that is, the average distance between any pair of classes is very small even when coupling is low and cohesion is high. In addition, the structure of OO software is a very heterogeneous network characterized by a degree distribution following a power-law with similar exponents. We have investigated the origin of these universal patterns. Our study suggests that some features of OO programing languages, like encapsulation, seem to be largely responsible for the small-world behavior. On the other hand, software heterogeneity is largely independent of the purpose and objectives of the particular system under study and appears to be related to a pattern of constrained growth. A number of software engineering topics may benefit from the present approach, including empirical software measurement and program comprehension.

cond-mat.dis-nn↗

arXiv2006

Life cycle of a minimal protocell - a dissipative particle dynamics (DPD) study

Cross-reactions and other systematic issues generated by the coupling of functional chemical subsystems pose the largest challenge for assembling a viable protocell in the laboratory. Our current work seeks to identify and clarify such key issues as we represent and analyze in simulation a full implementation of a minimal protocell. Using a 3D dissipative particle dynamics (DPD) simulation method we are able to address the coupled diffusion, self-assembly, and chemical reaction processes, required to model a full life cycle of the protocell, the protocell being composed of coupled genetic, metabolic, and container subsystems. Utilizing this minimal structural and functional representation of the constituent molecules, their interactions, and their reactions, we identify and explore the nature of the many linked processes for the full protocellular system.

nlin.AO↗

arXiv2006

Protocell Self-Reproduction in a Spatially Extended Metabolism-Vesicle System

Cellular life requires the presence of a set of biochemical mechanisms in order to maintain a predictable process of growth and division. Several attempts have been made towards the building of minimal protocells from a top-down approach, i.e. by using available biomolecules This type of synthetic approach has so far been unsuccesful, and the lack of appropriate models of the synthetic protocell cycle might be needed to guide future experiments. In this paper we present a simple biochemically and physically feasible model of cell replication involving a discrete semi-permeable vesicle with an internal minimal metabolism involving two reactive centers. It is shown that such a system can effectively undergo a whole cell replication cycle. The model can be used as a basic framework to model whole protocell dynamics including more complex sets of reactions. The possible implementation of our design in future synthetic protocells is outlined.

q-bio.CB↗

arXiv2006

Emergent Behavior in Agent Networks: Self-Organization in Wasp and Open Source Communities

Understanding the complex dynamics of communities of software developers requires a view of such organizations as a network of interacting agents involving both goals and constraints. Beyond their special features, these systems display some overall patterns of organization not far from the ones seen in other types of organizations, including both natural and artificial entities. By looking at both software developers and social insects as agents interacting in a complex network, we found common statistical patterns of organization. Here, simple self-organizing processes leading to the formation of hierarchies in wasp colonies and open source communities are studied. Our analysis further validates simple models of formation of wasp hierarchies based on individual learning. In the open source community, a few members are clearly distinguished from the rest of the community with different reinforcement mechanisms.

physics.soc-ph↗

arXiv2006

Evolving Social Weighted Networks: Nonlocal Dynamics of Open Source Communities

Complex networks emerge under different conditions through simple rules of growth and evolution. Such rules are typically local when dealing with biological systems and most social webs. An important deviation from such scenario is provided by communities of agents engaged in technology development, such as open source (OS) communities. Here we analyze their network structure, showing that it defines a complex weighted network with scaling laws at different levels, as measured by looking at e-mail exchanges. We also present a simple model of network growth involving non-local rules based on betweenness centrality. The model outcomes fit very well the observed scaling laws, suggesting that the overall goals of the community and the underlying hierarchical organization play a key role is shaping its dynamics.

physics.soc-ph↗

arXiv2005

Logarithmic growth dynamics in software networks

In a recent paper, Krapivsky and Redner (Phys. Rev. E, 71 (2005) 036118) proposed a new growing network model with new nodes being attached to a randomly selected node, as well to all ancestors of the target node. The model leads to a sparse graph with an average degree growing logarithmically with the system size. Here we present compeling evidence for software networks being the result of a similar class of growing dynamics. The predicted pattern of network growth, as well as the stationary in- and out-degree distributions are consistent with the model. Our results confirm the view of large-scale software topology being generated through duplication-rewiring mechanisms. Implications of these findings are outlined.

physics.soc-ph↗

arXiv2004

The large-scale organization of chemical reaction networks in astrophysics

The large-scale organization of complex networks, both natural and artificial, has shown the existence of highly heterogeneous patterns of organization. Such patterns typically involve scale-free degree distributions and small world, modular architectures. One example is provided by chemical reaction networks, such as the metabolic pathways. The chemical reactions of the Earth's atmosphere have also been shown to give rise to a scale-free network. Here we present novel data analysis on the structure of several astrophysical networks including the chemistry of the planetary atmospheres and the interstellar medium. Our work reveals that Earth's atmosphere displays a hierarchical organization, close to the one observed in cellular webs. Instead, the other astrophysical reaction networks reveal a much simpler pattern consistent with an equilibrium state. The implications for large-scale regulation of the planetary dynamics are outlined.

cond-mat.dis-nn↗

arXiv2004

Internet's Critical Path Horizon

Internet is known to display a highly heterogeneous structure and complex fluctuations in its traffic dynamics. Congestion seems to be an inevitable result of user's behavior coupled to the network dynamics and it effects should be minimized by choosing appropriate routing strategies. But what are the requirements of routing depth in order to optimize the traffic flow? In this paper we analyse the behavior of Internet traffic with a topologically realistic spatial structure as described in a previous study (S-H. Yook et al. ,Proc. Natl Acad. Sci. USA, {\bf 99} (2002) 13382). The model involves self-regulation of packet generation and different levels of routing depth. It is shown that it reproduces the relevant key, statistical features of Internet's traffic. Moreover, we also report the existence of a critical path horizon defining a transition from low-efficient traffic to highly efficient flow. This transition is actually a direct consequence of the web's small world architecture exploited by the routing algorithm. Once routing tables reach the network diameter, the traffic experiences a sudden transition from a low-efficient to a highly-efficient behavior. It is conjectured that routing policies might have spontaneously reached such a compromise in a distributed manner. Internet would thus be operating close to such critical path horizon.

cond-mat.dis-nn↗

arXiv2003

Modularity "for free" in genome architecture?

Background: Recent models of genome-proteome evolution have shown that some of the key traits displayed by the global structure of cellular networks might be a natural result of a duplication-diversification (DD) process. One of the consequences of such evolution is the emergence of a small world architecture together with a scale-free distribution of interactions. Here we show that the domain of parameter space were such structure emerges is related to a phase transition phenomenon. At this transition point, modular architecture spontaneously emerges as a byproduct of the DD process. Results: Although the DD models lack any functionality and are thus free from meeting functional constraints, they show the observed features displayed by the real proteome maps when tuned close to a sharp transition point separating a highly connected graph from a disconnected system. Close to such boundary, the maps are shown to display scale-free hierarchical organization, behave as small worlds and exhibit modularity. Conclusions: It is conjectured that natural selection tuned the average connectivity in such a way that the network reaches a sparse graph of connections. One consequence of such scenario is that the scaling laws and the essential ingredients for building a modular net emerge for free close to such transition.

q-bio.GN↗

arXiv2003

The Role of Computation in Complex Regulatory Networks

Biological phenomena differ significantly from physical phenomena. At the heart of this distinction is the fact that biological entities have computational abilities and thus they are inherently difficult to predict. This is the reason why simplified models that provide the minimal requirements for computation turn out to be very useful to study networks of many components. In this chapter, we briefly review the dynamical aspects of models of regulatory networks, discussing their most salient features, and we also show how these models can give clues about the way in which networks may organize their capacity to evolve, by providing simple examples of the implementation of robustness and modularity.

q-bio.MN↗

arXiv2003

Adaptive walks in a gene network model of morphogenesis: insights into the Cambrian explosion

The emergence of complex patterns of organization close to the Cambrian boundary is known to have happened over a (geologically) short period of time. It involved the rapid diversification of body plans and stands as one of the major transitions in evolution. How it took place is a controversial issue. Here we explore this problem by considering a simple model of pattern formation in multicellular organisms. By modeling gene network-based morphogenesis and its evolution through adaptive walks, we explore the question of how combinatorial explosions might have been actually involved in the Cambrian event. Here we show that a small amount of genetic complexity including both gene regulation and cell-cell signaling allows one to generate an extraordinary repertoire of stable spatial patterns of gene expression compatible with observed anteroposterior patterns in early development of metazoans. The consequences for the understanding of the tempo and mode of the Cambrian event are outlined.

q-bio.GN↗

arXiv2002

A model of large-scale proteome evolution

The next step in the understanding of the genome organization, after the determination of complete sequences, involves proteomics. The proteome includes the whole set of protein-protein interactions, and two recent independent studies have shown that its topology displays a number of surprising features shared by other complex networks, both natural and artificial. In order to understand the origins of this topology and its evolutionary implications, we present a simple model of proteome evolution that is able to reproduce many of the observed statistical regularities reported from the analysis of the yeast proteome. Our results suggest that the observed patterns can be explained by a process of gene duplication and diversification that would evolve proteome networks under a selection pressure, favoring robustness against failure of its individual components.

cond-mat.stat-mech↗

arXiv2001

Field theory for a reaction-diffusion model of quasispecies dynamics

RNA viruses are known to replicate with extremely high mutation rates. These rates are actually close to the so-called error threshold. This threshold is in fact a critical point beyond which genetic information is lost through a second-order phase transition, which has been dubbed the ``error catastrophe.'' Here we explore this phenomenon using a field theory approximation to the spatially extended Swetina-Schuster quasispecies model [J. Swetina and P. Schuster, Biophys. Chem. {\bf 16}, 329 (1982)], a single-sharp-peak landscape. In analogy with standard absorbing-state phase transitions, we develop a reaction-diffusion model whose discrete rules mimic the Swetina-Schuster model. The field theory representation of the reaction-diffusion system is constructed. The proposed field theory belongs to the same universality class than a conserved reaction-diffusion model previously proposed [F. van Wijland {\em et al.}, Physica A {\bf 251}, 179 (1998)]. From the field theory, we obtain the full set of exponents that characterize the critical behavior at the error threshold. Our results present the error catastrophe from a new point of view and suggest that spatial degrees of freedom can modify several mean field predictions previously considered, leading to the definition of characteristic exponents that could be experimentally measurable.

cond-mat.stat-mech↗

arXiv2000

A mean field stochastic theory for species-rich assembled communities

A dynamical model of an ecological community is analyzed within a "mean-field approximation" in which one of the species interacts with the combination of all of the other species in the community. Within this approximation the model may be formulated as a master equation describing a one-step stochastic process. The stationary distribution is obtained in closed form and is shown to reduce to a logseries or lognormal distribution, depending on the values that the parameters describing the model take on. A hyperbolic relationship between the connectance of the matrix of interspecies interactions and the average number of species, exists for a range of parameter values. The time evolution of the model at short and intermediate times is analyzed using van Kampen's approximation, which is valid when the number of individuals in the community is large. Good agreement with numerical simulations is found. The large time behavior, and the approach to the stationary state, is obtained by solving the equation for the generating function of the probability distribution. The analytical results which follow from the analysis are also in good agreement with direct simulations of the model.

nlin.AO↗

arXiv1999

Statistical measures of complexity for strongly interacting systems

In recent studies, new measures of complexity for nonlinear systems have been proposed based on probabilistic grounds, as the LMC measure (Phys. Lett. A {\bf 209} (1995) 321) or the SDL measure (Phys. Rev. E {\bf 59} (1999) 2). All these measures share an intuitive consideration: complexity seems to emerge in nature close to instability points, as for example the phase transition points characteristic of critical phenomena. Here we discuss these measures and their reliability for detecting complexity close to critical points in complex systems composed of many interacting units. Both a two-dimensional spatially extended problem (the 2D Ising model) and a $\infty$-dimensional (random graph) model (random Boolean networks) are analysed. It is shown that the LMC and the SDL measures can be easily generalized to extended systems but fails to detect real complexity.

adap-org↗

arXiv1999

Scaling in a Multispecies Network Model Ecosystem

A new model ecosystem consisting of many interacting species is introduced. The species are connected through a random matrix with a given connectivity. It is shown that the system is organized close to a boundary of marginal stability in such a way that fluctuations follow power law distributions both in species abundance and their lifetimes for some slow-driving (immigration) regime. The connectivity and the number of species are linked through a scaling relation which is the one observed in real ecosystems. These results suggest that the basic macroscopic features of real, species-rich ecologies might be linked with a critical state. A natural link between lognormal and power law distributions of species abundances is suggested.

adap-org↗